Load Data from the Clock Calculator

1. Table with summarize info [table 1]

1.1. Description of study population (all visits)

Baseline characteristics (confounders)

Overall
(N=129)
Age
Mean (SD) 57.6 (14.5)
Median (IQR) 60.0 (23.0)
BMI
Mean (SD) 22.0 (3.47)
Median (IQR) 21.8 (3.92)
factor(county)
Fuyuan 63 (48.8%)
Xuanwe 66 (51.2%)
factor(ses)
0 71 (55.0%)
1 58 (45.0%)
factor(edu)
1 90 (69.8%)
2 20 (15.5%)
3 14 (10.9%)
4 5 (3.9%)

Epigenetic ages

Overall
(N=129)
DNAmAge
Mean (SD) 57.6 (13.1)
Median (IQR) 59.4 (21.0)
DNAmAgeHannum
Mean (SD) 60.4 (13.9)
Median (IQR) 61.8 (22.8)
DNAmPhenoAge
Mean (SD) 56.2 (13.5)
Median (IQR) 58.0 (20.5)
DNAmAgeSkinBloodClock
Mean (SD) 57.1 (12.7)
Median (IQR) 59.8 (20.9)
DNAmGrimAge
Mean (SD) 56.2 (11.3)
Median (IQR) 57.6 (17.7)
DNAmTL
Mean (SD) 6.82 (0.321)
Median (IQR) 6.82 (0.452)

Epigenetic ages accelarations

Overall
(N=129)
AgeAccelerationResidual
Mean (SD) 0.359 (4.63)
Median (IQR) 0.140 (5.83)
AgeAccelerationResidualHannum
Mean (SD) -0.235 (4.01)
Median (IQR) -0.376 (4.64)
AgeAccelPheno
Mean (SD) -0.397 (4.28)
Median (IQR) -0.732 (5.28)
DNAmAgeSkinBloodClockAdjAge
Mean (SD) 0.170 (3.41)
Median (IQR) 0.435 (3.59)
AgeAccelGrim
Mean (SD) -0.440 (2.94)
Median (IQR) -0.659 (3.20)
DNAmTLAdjAge
Mean (SD) 0.0277 (0.180)
Median (IQR) 0.0305 (0.234)
IEAA
Mean (SD) 0.179 (4.24)
Median (IQR) 0.136 (5.56)
EEAA
Mean (SD) -0.296 (5.11)
Median (IQR) -0.174 (6.56)

Fuel/stove type exposures

Overall
(N=129)
factor(curFuel)
Smokeles 18 (14.0%)
Smoky 98 (76.0%)
Wood_and_or_Plant 13 (10.1%)
factor(brthFuel)
Mix 54 (41.9%)
Outside of XW/FY 3 (2.3%)
Smokeles 7 (5.4%)
Smoky 52 (40.3%)
Wood 13 (10.1%)
factor(childFuel)
Mix 63 (48.8%)
Smokeles 5 (3.9%)
Smoky 50 (38.8%)
Wood 11 (8.5%)
factor(curFuel_detail)
Plant 4 (3.1%)
Smokeles 18 (14.0%)
Smoky 98 (76.0%)
Wood 9 (7.0%)
factor(cumFuel)
Mix 84 (65.1%)
Smokeles 1 (0.8%)
Smoky 42 (32.6%)
Wood 2 (1.6%)
factor(curStove)
Firepit_and_unventilated 22 (17.1%)
Mix 19 (14.7%)
Portable_stove 20 (15.5%)
Ventilated 51 (39.5%)
Missing 17 (13.2%)

5MC exposures

Overall
(N=129)
cur_5mc
Mean (SD) 8.15 (4.23)
Median (IQR) 8.26 (4.48)
Missing 3 (2.3%)
cum_5mc
Mean (SD) 275 (150)
Median (IQR) 257 (209)
Missing 3 (2.3%)
bir_5mc
Mean (SD) 5.22 (2.82)
Median (IQR) 4.75 (5.34)
Missing 3 (2.3%)
cur_5mc_measured
Mean (SD) 12.8 (38.1)
Median (IQR) 5.52 (6.17)
Missing 78 (60.5%)
## [1] "Pearson pair-wise correlation:"
##                    cur_5mc   cum_5mc     bir_5mc cur_5mc_measured
## cur_5mc          1.0000000 0.7025515  0.63724241       0.13319188
## cum_5mc          0.7025515 1.0000000  0.81021435       0.18607788
## bir_5mc          0.6372424 0.8102143  1.00000000      -0.03066466
## cur_5mc_measured 0.1331919 0.1860779 -0.03066466       1.00000000
## [1] "Spearman pair-wise correlation:"
##                    cur_5mc   cum_5mc   bir_5mc cur_5mc_measured
## cur_5mc          1.0000000 0.6487685 0.5771252        0.4692482
## cum_5mc          0.6487685 1.0000000 0.7918033        0.3290434
## bir_5mc          0.5771252 0.7918033 1.0000000        0.2804710
## cur_5mc_measured 0.4692482 0.3290434 0.2804710        1.0000000

Cluster-based exposures

clusCUR6

Clusters based on model-based exposure estimates at or shortly before the visit

Overall
(N=129)
CUR6_BC_PAH6
Mean (SD) 0.194 (1.00)
Median (IQR) 0.799 (1.36)
Missing 3 (2.3%)
CUR6_PAH31
Mean (SD) 0.192 (1.00)
Median (IQR) 0.437 (1.09)
Missing 3 (2.3%)
CUR6_NkF
Mean (SD) -0.0817 (1.00)
Median (IQR) -0.302 (1.20)
Missing 3 (2.3%)
CUR6_PM_RET
Mean (SD) -0.0374 (1.00)
Median (IQR) -0.316 (0.929)
Missing 3 (2.3%)
CUR6_NO2
Mean (SD) 0.123 (1.00)
Median (IQR) 0.0189 (1.22)
Missing 3 (2.3%)
CUR6_SO2
Mean (SD) -0.152 (1.00)
Median (IQR) -0.335 (1.16)
Missing 3 (2.3%)

clusCHLD5

Clusters based on model-based exposure estimates accrued before age 18

Overall
(N=129)
CHLD5_X7
Mean (SD) -0.0382 (1.00)
Median (IQR) 0.111 (1.10)
Missing 3 (2.3%)
CHLD5_X33
Mean (SD) 0.155 (1.00)
Median (IQR) 0.00445 (1.67)
Missing 3 (2.3%)
CHLD5_NkF
Mean (SD) -0.0978 (1.00)
Median (IQR) -0.220 (1.34)
Missing 3 (2.3%)
CHLD5_NO2
Mean (SD) 0.167 (1.00)
Median (IQR) 0.196 (1.16)
Missing 3 (2.3%)
CHLD5_SO2
Mean (SD) 0.00157 (1.00)
Median (IQR) 0.362 (1.55)
Missing 3 (2.3%)

clusCUM6

Clusters based on model-based lifetime exposure estimates

Overall
(N=129)
CUM6_BC_NO2_PM
Mean (SD) 0.114 (1.00)
Median (IQR) 0.281 (1.44)
Missing 3 (2.3%)
CUM6_PAH36
Mean (SD) 0.199 (1.00)
Median (IQR) 0.254 (1.77)
Missing 3 (2.3%)
CUM6_DlP
Mean (SD) -0.175 (1.00)
Median (IQR) -0.459 (1.71)
Missing 3 (2.3%)
CUM6_NkF
Mean (SD) -0.0183 (1.00)
Median (IQR) -0.0813 (1.10)
Missing 3 (2.3%)
CUM6_RET
Mean (SD) -0.125 (1.00)
Median (IQR) -0.215 (1.11)
Missing 3 (2.3%)
CUM6_SO2
Mean (SD) -0.0834 (1.00)
Median (IQR) 0.0951 (1.20)
Missing 3 (2.3%)

clusMEAS6

Clusters based on pollutant measurements

Overall
(N=129)
MEAS6_BC_PM_RET
Mean (SD) -0.0486 (1.00)
Median [Min, Max] -0.104 [-2.12, 2.58]
Missing 64 (49.6%)
MEAS6_X31
Mean (SD) -0.00352 (1.00)
Median [Min, Max] 0.125 [-1.94, 2.13]
Missing 64 (49.6%)
MEAS6_X5
Mean (SD) 0.0136 (1.00)
Median [Min, Max] -0.102 [-1.42, 1.75]
Missing 64 (49.6%)
MEAS6_DlP
Mean (SD) 0.0186 (1.00)
Median [Min, Max] -0.627 [-1.02, 1.76]
Missing 64 (49.6%)
MEAS6_NkF
Mean (SD) 0.00902 (1.00)
Median [Min, Max] -0.489 [-1.18, 1.85]
Missing 64 (49.6%)
MEAS6_NO2_SO2
Mean (SD) 0.0902 (1.00)
Median [Min, Max] -0.0368 [-1.56, 2.06]
Missing 64 (49.6%)

clusURI5

Clusters based on urinary biomarkers

Overall
(N=129)
URI5_NAP_1M_2M
Mean (SD) 0.0150 (1.00)
Median (IQR) 0.0747 (1.26)
Missing 25 (19.4%)
URI5_ACE
Mean (SD) -0.0574 (1.00)
Median (IQR) -0.0912 (1.31)
Missing 25 (19.4%)
URI5_FLU_PHE
Mean (SD) -0.0484 (1.00)
Median (IQR) 0.0355 (1.32)
Missing 25 (19.4%)
URI5_PYR
Mean (SD) -0.0201 (1.00)
Median (IQR) 0.0727 (0.825)
Missing 25 (19.4%)
URI5_CHR
Mean (SD) -0.0112 (1.00)
Median (IQR) -0.0392 (0.957)
Missing 25 (19.4%)

Ambient exposures

Overall
(N=129)
bap_air
Mean (SD) 65.4 (86.9)
Median (IQR) 39.4 (55.7)
Missing 5 (3.9%)
pm25_air
Mean (SD) 197 (176)
Median (IQR) 140 (132)
ANY_air
Mean (SD) 1040 (1790)
Median (IQR) 552 (645)
Missing 41 (31.8%)
BPE_air
Mean (SD) 70.6 (92.0)
Median (IQR) 45.5 (53.1)
Missing 5 (3.9%)
BaA_air
Mean (SD) 87.8 (145)
Median (IQR) 40.5 (74.9)
Missing 5 (3.9%)
BbF_air
Mean (SD) 106 (143)
Median (IQR) 60.6 (89.3)
Missing 5 (3.9%)
BkF_air
Mean (SD) 23.3 (31.7)
Median (IQR) 13.4 (20.1)
Missing 5 (3.9%)
CHR_air
Mean (SD) 83.3 (133)
Median (IQR) 42.7 (73.6)
Missing 5 (3.9%)
DBA_air
Mean (SD) 23.9 (35.9)
Median (IQR) 12.7 (23.1)
Missing 5 (3.9%)
FLT_air
Mean (SD) 59.6 (136)
Median (IQR) 15.6 (37.9)
Missing 5 (3.9%)
FLU_air
Mean (SD) 486 (680)
Median (IQR) 273 (372)
Missing 41 (31.8%)
IPY_air
Mean (SD) 43.0 (51.1)
Median (IQR) 28.1 (34.8)
Missing 5 (3.9%)
NAP_air
Mean (SD) 5730 (8740)
Median (IQR) 3140 (3720)
Missing 41 (31.8%)
PHE_air
Mean (SD) 730 (1050)
Median (IQR) 388 (612)
Missing 41 (31.8%)
PYR_air
Mean (SD) 66.2 (139)
Median (IQR) 17.9 (49.0)
Missing 5 (3.9%)

Urinary biomarkers

Overall
(N=129)
Benzanthracene_Chrysene_urine
Mean (SD) 0.919 (3.17)
Median (IQR) 0.384 (0.487)
Missing 2 (1.6%)
Naphthalene_urine
Mean (SD) 224 (686)
Median (IQR) 111 (111)
Methylnaphthalene_2_urine
Mean (SD) 45.8 (59.4)
Median (IQR) 29.7 (30.6)
Missing 9 (7.0%)
Methylnaphthalene_1_urine
Mean (SD) 19.7 (24.5)
Median (IQR) 11.6 (18.1)
Missing 4 (3.1%)
Acenaphthene_urine
Mean (SD) 7.40 (10.7)
Median (IQR) 3.21 (5.57)
Phenanthrene_Anthracene_urine
Mean (SD) 204 (275)
Median (IQR) 115 (194)
Fluoranthene_urine
Mean (SD) 21.0 (23.4)
Median (IQR) 17.1 (17.3)
Pyrene_urine
Mean (SD) 0.715 (0.574)
Median (IQR) 0.552 (0.411)
Missing 18 (14.0%)

1.2. Description of study population (first visit for all objects)

There are 129 visits with corresponding epigenetic ages available among 106 female subjects. For these 106 subjects, 83 have been visited once and 23 have been visited twice.

The following tables summarize all the information of the first visit of these 106 subjects.

Baseline characteristics (confounders)

Overall
(N=106)
Age
Mean (SD) 56.2 (15.0)
Median (IQR) 58.0 (24.8)
BMI
Mean (SD) 22.0 (3.46)
Median (IQR) 21.7 (4.46)
factor(county)
Fuyuan 53 (50.0%)
Xuanwe 53 (50.0%)
factor(ses)
0 53 (50.0%)
1 53 (50.0%)
factor(edu)
1 72 (67.9%)
2 17 (16.0%)
3 13 (12.3%)
4 4 (3.8%)

Epigenetic ages

Overall
(N=106)
DNAmAge
Mean (SD) 56.3 (13.5)
Median (IQR) 57.6 (22.0)
DNAmAgeHannum
Mean (SD) 59.0 (14.4)
Median (IQR) 59.9 (23.7)
DNAmPhenoAge
Mean (SD) 54.7 (14.0)
Median (IQR) 54.8 (21.6)
DNAmAgeSkinBloodClock
Mean (SD) 55.8 (13.2)
Median (IQR) 57.6 (23.5)
DNAmGrimAge
Mean (SD) 55.3 (11.8)
Median (IQR) 57.2 (19.4)
DNAmTL
Mean (SD) 6.84 (0.329)
Median (IQR) 6.85 (0.461)

Epigenetic ages accelarations

Overall
(N=106)
AgeAccelerationResidual
Mean (SD) 0.182 (4.62)
Median (IQR) 0.213 (5.90)
AgeAccelerationResidualHannum
Mean (SD) -0.435 (4.06)
Median (IQR) -0.432 (4.79)
AgeAccelPheno
Mean (SD) -0.746 (4.45)
Median (IQR) -1.06 (5.61)
DNAmAgeSkinBloodClockAdjAge
Mean (SD) -0.000985 (3.43)
Median (IQR) 0.380 (3.58)
AgeAccelGrim
Mean (SD) -0.320 (2.96)
Median (IQR) -0.913 (3.27)
DNAmTLAdjAge
Mean (SD) 0.0307 (0.182)
Median (IQR) 0.0347 (0.238)
IEAA
Mean (SD) 0.0900 (4.34)
Median (IQR) 0.303 (5.90)
EEAA
Mean (SD) -0.534 (5.24)
Median (IQR) -0.425 (6.83)

Fuel/stove type exposures

Overall
(N=106)
factor(curFuel)
Smokeles 13 (12.3%)
Smoky 82 (77.4%)
Wood_and_or_Plant 11 (10.4%)
factor(brthFuel)
Mix 43 (40.6%)
Outside of XW/FY 3 (2.8%)
Smokeles 5 (4.7%)
Smoky 45 (42.5%)
Wood 10 (9.4%)
factor(childFuel)
Mix 50 (47.2%)
Smokeles 4 (3.8%)
Smoky 43 (40.6%)
Wood 9 (8.5%)
factor(curFuel_detail)
Plant 4 (3.8%)
Smokeles 13 (12.3%)
Smoky 82 (77.4%)
Wood 7 (6.6%)
factor(cumFuel)
Mix 66 (62.3%)
Smokeles 1 (0.9%)
Smoky 37 (34.9%)
Wood 2 (1.9%)
factor(curStove)
Firepit_and_unventilated 16 (15.1%)
Mix 14 (13.2%)
Portable_stove 16 (15.1%)
Ventilated 44 (41.5%)
Missing 16 (15.1%)

5MC exposures

Overall
(N=106)
cur_5mc
Mean (SD) 8.13 (4.14)
Median (IQR) 7.61 (4.48)
Missing 2 (1.9%)
cum_5mc
Mean (SD) 266 (149)
Median (IQR) 236 (194)
Missing 2 (1.9%)
bir_5mc
Mean (SD) 5.14 (2.81)
Median (IQR) 4.73 (5.23)
Missing 2 (1.9%)
cur_5mc_measured
Mean (SD) 13.7 (40.7)
Median (IQR) 5.71 (5.83)
Missing 62 (58.5%)
## [1] "Pearson pair-wise correlation:"
##                    cur_5mc   cum_5mc     bir_5mc cur_5mc_measured
## cur_5mc          1.0000000 0.6947332  0.67276560       0.10959754
## cum_5mc          0.6947332 1.0000000  0.83239536       0.17329428
## bir_5mc          0.6727656 0.8323954  1.00000000      -0.05013945
## cur_5mc_measured 0.1095975 0.1732943 -0.05013945       1.00000000
## [1] "Spearman pair-wise correlation:"
##                    cur_5mc   cum_5mc   bir_5mc cur_5mc_measured
## cur_5mc          1.0000000 0.6291806 0.6239118        0.4534635
## cum_5mc          0.6291806 1.0000000 0.8206830        0.3159166
## bir_5mc          0.6239118 0.8206830 1.0000000        0.2008400
## cur_5mc_measured 0.4534635 0.3159166 0.2008400        1.0000000

Cluster-based exposures

clusCUR6

Clusters based on model-based exposure estimates at or shortly before the visit

Overall
(N=106)
CUR6_BC_PAH6
Mean (SD) 0.222 (0.975)
Median (IQR) 0.799 (1.21)
Missing 2 (1.9%)
CUR6_PAH31
Mean (SD) 0.205 (0.977)
Median (IQR) 0.433 (1.10)
Missing 2 (1.9%)
CUR6_NkF
Mean (SD) -0.0581 (0.985)
Median (IQR) -0.297 (1.20)
Missing 2 (1.9%)
CUR6_PM_RET
Mean (SD) -0.0120 (1.01)
Median (IQR) -0.298 (0.947)
Missing 2 (1.9%)
CUR6_NO2
Mean (SD) 0.0752 (1.00)
Median (IQR) -0.0204 (1.14)
Missing 2 (1.9%)
CUR6_SO2
Mean (SD) -0.205 (0.995)
Median (IQR) -0.335 (1.16)
Missing 2 (1.9%)

clusCHLD5

Clusters based on model-based exposure estimates accrued before age 18

Overall
(N=106)
CHLD5_X7
Mean (SD) -0.0684 (0.965)
Median (IQR) 0.0837 (0.991)
Missing 2 (1.9%)
CHLD5_X33
Mean (SD) 0.126 (0.995)
Median (IQR) -0.0314 (1.65)
Missing 2 (1.9%)
CHLD5_NkF
Mean (SD) -0.0960 (0.992)
Median (IQR) -0.203 (1.36)
Missing 2 (1.9%)
CHLD5_NO2
Mean (SD) 0.119 (1.02)
Median (IQR) 0.196 (1.18)
Missing 2 (1.9%)
CHLD5_SO2
Mean (SD) -0.0588 (1.00)
Median (IQR) 0.355 (1.57)
Missing 2 (1.9%)

clusCUM6

Clusters based on model-based lifetime exposure estimates

Overall
(N=106)
CUM6_BC_NO2_PM
Mean (SD) 0.0305 (1.04)
Median (IQR) 0.164 (1.71)
Missing 2 (1.9%)
CUM6_PAH36
Mean (SD) 0.141 (0.995)
Median (IQR) 0.147 (1.65)
Missing 2 (1.9%)
CUM6_DlP
Mean (SD) -0.196 (1.00)
Median (IQR) -0.445 (1.70)
Missing 2 (1.9%)
CUM6_NkF
Mean (SD) -0.0526 (1.02)
Median (IQR) -0.150 (1.23)
Missing 2 (1.9%)
CUM6_RET
Mean (SD) -0.156 (1.01)
Median (IQR) -0.249 (1.12)
Missing 2 (1.9%)
CUM6_SO2
Mean (SD) -0.175 (1.00)
Median (IQR) -0.0667 (1.62)
Missing 2 (1.9%)

clusMEAS6

Clusters based on pollutant measurements

Overall
(N=106)
MEAS6_BC_PM_RET
Mean (SD) 0.000103 (0.962)
Median [Min, Max] 0.0484 [-2.12, 2.58]
Missing 57 (53.8%)
MEAS6_X31
Mean (SD) 0.0157 (0.910)
Median [Min, Max] 0.148 [-1.94, 2.13]
Missing 57 (53.8%)
MEAS6_X5
Mean (SD) 0.00979 (0.975)
Median [Min, Max] -0.102 [-1.42, 1.75]
Missing 57 (53.8%)
MEAS6_DlP
Mean (SD) -0.0238 (0.992)
Median [Min, Max] -0.640 [-1.02, 1.76]
Missing 57 (53.8%)
MEAS6_NkF
Mean (SD) 0.0443 (1.02)
Median [Min, Max] -0.489 [-1.18, 1.85]
Missing 57 (53.8%)
MEAS6_NO2_SO2
Mean (SD) 0.0300 (0.989)
Median [Min, Max] -0.114 [-1.56, 2.06]
Missing 57 (53.8%)

clusURI5

Clusters based on urinary biomarkers

Overall
(N=106)
URI5_NAP_1M_2M
Mean (SD) 0.0130 (1.01)
Median (IQR) 0.0739 (1.24)
Missing 13 (12.3%)
URI5_ACE
Mean (SD) -0.118 (0.997)
Median (IQR) -0.125 (1.35)
Missing 13 (12.3%)
URI5_FLU_PHE
Mean (SD) -0.0444 (1.00)
Median (IQR) 0.0608 (1.31)
Missing 13 (12.3%)
URI5_PYR
Mean (SD) -0.0612 (1.03)
Median (IQR) 0.0734 (0.925)
Missing 13 (12.3%)
URI5_CHR
Mean (SD) -0.0236 (1.02)
Median (IQR) -0.0342 (0.950)
Missing 13 (12.3%)

Ambient exposures

Overall
(N=106)
bap_air
Mean (SD) 66.3 (90.5)
Median (IQR) 39.5 (55.9)
Missing 3 (2.8%)
pm25_air
Mean (SD) 205 (188)
Median (IQR) 144 (133)
ANY_air
Mean (SD) 908 (1540)
Median (IQR) 486 (651)
Missing 33 (31.1%)
BPE_air
Mean (SD) 69.2 (93.1)
Median (IQR) 40.8 (51.7)
Missing 3 (2.8%)
BaA_air
Mean (SD) 91.3 (153)
Median (IQR) 43.7 (76.8)
Missing 3 (2.8%)
BbF_air
Mean (SD) 110 (151)
Median (IQR) 64.7 (92.2)
Missing 3 (2.8%)
BkF_air
Mean (SD) 23.5 (33.2)
Median (IQR) 13.2 (19.5)
Missing 3 (2.8%)
CHR_air
Mean (SD) 88.0 (141)
Median (IQR) 48.6 (74.5)
Missing 3 (2.8%)
DBA_air
Mean (SD) 23.1 (35.9)
Median (IQR) 11.0 (22.4)
Missing 3 (2.8%)
FLT_air
Mean (SD) 65.2 (146)
Median (IQR) 17.5 (41.0)
Missing 3 (2.8%)
FLU_air
Mean (SD) 441 (691)
Median (IQR) 250 (260)
Missing 33 (31.1%)
IPY_air
Mean (SD) 40.9 (49.7)
Median (IQR) 27.1 (33.5)
Missing 3 (2.8%)
NAP_air
Mean (SD) 5340 (8070)
Median (IQR) 3020 (3540)
Missing 33 (31.1%)
PHE_air
Mean (SD) 675 (1080)
Median (IQR) 351 (533)
Missing 33 (31.1%)
PYR_air
Mean (SD) 71.3 (149)
Median (IQR) 21.3 (50.6)
Missing 3 (2.8%)

Urinary biomarkers

Overall
(N=106)
Benzanthracene_Chrysene_urine
Mean (SD) 0.976 (3.49)
Median (IQR) 0.389 (0.465)
Missing 2 (1.9%)
Naphthalene_urine
Mean (SD) 247 (755)
Median (IQR) 113 (112)
Methylnaphthalene_2_urine
Mean (SD) 48.7 (64.7)
Median (IQR) 29.8 (29.4)
Missing 8 (7.5%)
Methylnaphthalene_1_urine
Mean (SD) 21.0 (26.4)
Median (IQR) 12.0 (18.7)
Missing 3 (2.8%)
Acenaphthene_urine
Mean (SD) 7.76 (11.4)
Median (IQR) 3.34 (5.84)
Phenanthrene_Anthracene_urine
Mean (SD) 216 (296)
Median (IQR) 116 (191)
Fluoranthene_urine
Mean (SD) 21.8 (25.1)
Median (IQR) 16.5 (17.5)
Pyrene_urine
Mean (SD) 0.744 (0.622)
Median (IQR) 0.552 (0.423)
Missing 15 (14.2%)

1.3. EAA ~ confounders

## For AgeAccelerationResidual :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      -0.2555 4.8412  -9.7443   9.2334 0.9579    > 0.05
## Age               0.0164 0.0416  -0.0651   0.0979 0.6940    > 0.05
## countyXuanwe     -0.3183 0.8670  -2.0175   1.3810 0.7135    > 0.05
## BMI              -0.0820 0.1092  -0.2961   0.1321 0.4528    > 0.05
## ses               1.9126 1.2040  -0.4472   4.2724 0.1122    > 0.05
## edu               0.4074 0.5870  -0.7431   1.5580 0.4876    > 0.05
## For AgeAccelerationResidualHannum :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      -4.0613 4.1892 -12.2720   4.1495 0.3323    > 0.05
## Age               0.0447 0.0389  -0.0316   0.1209 0.2508    > 0.05
## countyXuanwe      0.4064 0.7888  -1.1396   1.9523 0.6064    > 0.05
## BMI               0.0047 0.0903  -0.1722   0.1817 0.9584    > 0.05
## ses              -0.1213 1.2013  -2.4758   2.2332 0.9196    > 0.05
## edu               0.6429 0.5143  -0.3652   1.6509 0.2113    > 0.05
## For AgeAccelPheno :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      -2.6519 3.9910 -10.4742   5.1704 0.5064    > 0.05
## Age               0.0252 0.0403  -0.0537   0.1042 0.5315    > 0.05
## countyXuanwe     -0.4712 0.8431  -2.1237   1.1813 0.5763    > 0.05
## BMI               0.0553 0.0890  -0.1191   0.2298 0.5341    > 0.05
## ses              -0.2758 1.0826  -2.3976   1.8461 0.7989    > 0.05
## edu              -0.0725 0.5041  -1.0606   0.9155 0.8856    > 0.05
## For DNAmAgeSkinBloodClockAdjAge :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      -1.5906 3.7271  -8.8957   5.7146 0.6696    > 0.05
## Age              -0.0053 0.0399  -0.0835   0.0730 0.8954    > 0.05
## countyXuanwe     -0.0470 0.6577  -1.3361   1.2421 0.9431    > 0.05
## BMI               0.0846 0.0778  -0.0678   0.2371 0.2766    > 0.05
## ses              -0.2236 1.0918  -2.3634   1.9163 0.8377    > 0.05
## edu               0.1747 0.4783  -0.7627   1.1122 0.7149    > 0.05
## For AgeAccelGrim :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      -1.0505 2.4045  -5.7633   3.6623 0.6622    > 0.05
## Age               0.0539 0.0234   0.0080   0.0998 0.0214   <= 0.05
## countyXuanwe     -1.0738 0.5590  -2.1694   0.0218 0.0547    > 0.05
## BMI              -0.1189 0.0652  -0.2468   0.0089 0.0683    > 0.05
## ses               1.7585 0.7244   0.3387   3.1784 0.0152   <= 0.05
## edu              -0.0325 0.2801  -0.5815   0.5164 0.9076    > 0.05
## For DNAmTLAdjAge :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       0.2668 0.1305   0.0111   0.5226 0.0408   <= 0.05
## Age              -0.0030 0.0014  -0.0057  -0.0003 0.0274   <= 0.05
## countyXuanwe      0.0277 0.0351  -0.0411   0.0965 0.4301    > 0.05
## BMI              -0.0016 0.0041  -0.0095   0.0063 0.6937    > 0.05
## ses              -0.0198 0.0493  -0.1165   0.0769 0.6879    > 0.05
## edu              -0.0246 0.0152  -0.0545   0.0052 0.1056    > 0.05
## For IEAA :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       0.3629 4.8675  -9.1774   9.9031 0.9406    > 0.05
## Age               0.0186 0.0420  -0.0636   0.1009 0.6571    > 0.05
## countyXuanwe     -0.6249 0.7946  -2.1824   0.9325 0.4316    > 0.05
## BMI              -0.0702 0.1301  -0.3251   0.1848 0.5897    > 0.05
## ses               1.8296 1.2467  -0.6140   4.2732 0.1422    > 0.05
## edu              -0.2049 0.5077  -1.2000   0.7902 0.6866    > 0.05
## For EEAA :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      -6.8361 5.1177 -16.8669   3.1947 0.1816    > 0.05
## Age               0.0710 0.0476  -0.0223   0.1643 0.1358    > 0.05
## countyXuanwe      0.6297 1.0042  -1.3387   2.5980 0.5307    > 0.05
## BMI               0.0083 0.1160  -0.2190   0.2357 0.9428    > 0.05
## ses               0.2458 1.4845  -2.6640   3.1555 0.8685    > 0.05
## edu               1.2008 0.6229  -0.0202   2.4218 0.0539    > 0.05

1.4. 5MC ~ confounders

## For cur_5mc :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)      18.2037 4.7051   8.9817  27.4257 0.0001  <= 0.001
## Age              -0.0869 0.0348  -0.1551  -0.0187 0.0125   <= 0.05
## countyXuanwe      0.7541 0.7996  -0.8132   2.3213 0.3457    > 0.05
## BMI              -0.2026 0.1302  -0.4578   0.0526 0.1196    > 0.05
## ses              -1.6191 1.1106  -3.7958   0.5576 0.1449    > 0.05
## edu              -0.2050 0.4356  -1.0588   0.6488 0.6379    > 0.05
## For cum_5mc :[1] "Fitting with 129 observations."
##              coefficient      std ci_lower ci_upper  p_val sig_level
## (Intercept)     205.6981 132.0974 -53.2128 464.6090 0.1194    > 0.05
## Age               3.1286   1.0698   1.0318   5.2254 0.0034   <= 0.01
## countyXuanwe     22.2370  26.7781 -30.2481  74.7222 0.4063    > 0.05
## BMI              -3.7026   3.9015 -11.3496   3.9444 0.3426    > 0.05
## ses             -30.6554  34.5139 -98.3026  36.9919 0.3744    > 0.05
## edu             -20.3137  13.3902 -46.5585   5.9311 0.1293    > 0.05
## For bir_5mc :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       6.3683 1.9366   2.5726  10.1641 0.0010   <= 0.01
## Age              -0.0053 0.0217  -0.0478   0.0372 0.8072    > 0.05
## countyXuanwe      0.3936 0.5482  -0.6809   1.4681 0.4728    > 0.05
## BMI              -0.0093 0.0294  -0.0669   0.0483 0.7513    > 0.05
## ses              -0.0277 0.7455  -1.4889   1.4334 0.9703    > 0.05
## edu              -0.6050 0.2810  -1.1558  -0.0542 0.0313   <= 0.05
## For cur_5mc_measured :[1] "Fitting with 129 observations."
##              coefficient     std ci_lower ci_upper  p_val sig_level
## (Intercept)      19.5262 28.7109 -36.7471  75.7995 0.4964    > 0.05
## Age               0.1232  0.2459  -0.3588   0.6052 0.6164    > 0.05
## countyXuanwe     16.2821 13.7250 -10.6188  43.1830 0.2355    > 0.05
## BMI              -1.1442  1.1403  -3.3793   1.0908 0.3157    > 0.05
## ses              -8.6827 11.4173 -31.0606  13.6951 0.4470    > 0.05
## edu               4.9116  6.0670  -6.9797  16.8029 0.4182    > 0.05

1.5. clusCUR6 ~ confounders

## For CUR6_BC_PAH6 :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       0.1239 0.8209  -1.4851   1.7329 0.8800    > 0.05
## Age               0.0057 0.0075  -0.0089   0.0204 0.4413    > 0.05
## countyXuanwe      0.6264 0.1812   0.2713   0.9816 0.0005  <= 0.001
## BMI              -0.0186 0.0246  -0.0669   0.0296 0.4496    > 0.05
## ses               0.1084 0.2171  -0.3172   0.5340 0.6176    > 0.05
## edu              -0.1224 0.1193  -0.3563   0.1116 0.3053    > 0.05
## For CUR6_PAH31 :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       2.1788 1.0617   0.0980   4.2597 0.0401   <= 0.05
## Age              -0.0145 0.0086  -0.0313   0.0024 0.0920    > 0.05
## countyXuanwe      0.2369 0.1917  -0.1388   0.6125 0.2165    > 0.05
## BMI              -0.0478 0.0301  -0.1068   0.0112 0.1121    > 0.05
## ses              -0.2649 0.2421  -0.7394   0.2095 0.2738    > 0.05
## edu              -0.0632 0.1196  -0.2976   0.1712 0.5973    > 0.05
## For CUR6_NkF :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       1.7328 0.9649  -0.1584   3.6240 0.0725    > 0.05
## Age              -0.0143 0.0082  -0.0305   0.0018 0.0817    > 0.05
## countyXuanwe     -0.1208 0.1900  -0.4933   0.2516 0.5249    > 0.05
## BMI              -0.0414 0.0303  -0.1009   0.0180 0.1720    > 0.05
## ses              -0.1386 0.2636  -0.6554   0.3781 0.5990    > 0.05
## edu               0.0387 0.1199  -0.1963   0.2736 0.7469    > 0.05
## For CUR6_PM_RET :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       1.1110 0.8437  -0.5428   2.7647 0.1879    > 0.05
## Age              -0.0027 0.0108  -0.0239   0.0184 0.8016    > 0.05
## countyXuanwe     -0.3576 0.1966  -0.7430   0.0278 0.0689    > 0.05
## BMI              -0.0303 0.0208  -0.0711   0.0105 0.1450    > 0.05
## ses              -0.0712 0.3003  -0.6599   0.5174 0.8125    > 0.05
## edu              -0.0575 0.0978  -0.2492   0.1343 0.5567    > 0.05
## For CUR6_NO2 :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       0.5882 0.8110  -1.0014   2.1777 0.4683    > 0.05
## Age               0.0010 0.0077  -0.0141   0.0160 0.8997    > 0.05
## countyXuanwe     -0.7780 0.1836  -1.1379  -0.4181 0.0000  <= 0.001
## BMI               0.0004 0.0230  -0.0447   0.0454 0.9866    > 0.05
## ses              -0.2574 0.2255  -0.6994   0.1845 0.2536    > 0.05
## edu              -0.0300 0.1405  -0.3054   0.2453 0.8307    > 0.05
## For CUR6_SO2 :[1] "Fitting with 129 observations."
##              coefficient    std ci_lower ci_upper  p_val sig_level
## (Intercept)       0.5267 0.8807  -1.1996   2.2529 0.5499    > 0.05
## Age              -0.0080 0.0102  -0.0281   0.0120 0.4308    > 0.05
## countyXuanwe     -0.4910 0.1868  -0.8571  -0.1248 0.0086   <= 0.01
## BMI               0.0037 0.0109  -0.0177   0.0251 0.7365    > 0.05
## ses              -0.3921 0.2544  -0.8906   0.1065 0.1232    > 0.05
## edu               0.0577 0.1441  -0.2247   0.3401 0.6890    > 0.05

Fuel Types Summary table

Current Fuel vs Birth Fuel + Cumulative

##           brthFuel  cumFuel Smokeles Smoky Wood_and_or_Plant
## 1              Mix      Mix        9    38                 7
## 2 Outside of XW/FY      Mix        1     2                 0
## 3         Smokeles      Mix        2     4                 0
## 4         Smokeles Smokeles        0     1                 0
## 5            Smoky      Mix        3     7                 0
## 6            Smoky    Smoky        1    41                 0
## 7             Wood      Mix        2     5                 4
## 8             Wood     Wood        0     0                 2

2. PCA

3. Explore clocks

3.1. Clock values

3.2. Correlogram

Between clocks

All visits included

3.3. Median absolute error

##               DNAmAge         DNAmAgeHannum          DNAmPhenoAge 
##              3.455101              3.380488              3.005900 
## DNAmAgeSkinBloodClock           DNAmGrimAge 
##              2.585191              4.063720

3.4. Scatterplots of age vs each epigenetic age

4. Explore Exposure Measurements

4.1. Correlogram

4.1.1. Between Ambient Exposure Measurements

4.1.2. Between Urinary Exposure Measurements

4.1.3. Between Ambient and Urinary Exposure Measurements

4.1.4. Between Clustered Exposure Measurements

5. Clocks vs Measurements

5.1. Pairplots

5.1.1. Urinary Exposure Measurements

5.1.2. Ambient Exposure Measurements

5.1.3. Clustered Exposure Measurements